[CINN] Add symbolic select

paddle/cinn/hlir/dialect/operator/ir/ops.yaml

@@ -103,6 +103,16 @@
     func : scale
   interfaces : paddle::dialect::InferSymbolicShapeInterface
 
+- op : select
+  args : (Tensor condition, Tensor true_value, Tensor false_value )
+  output : Tensor(out)
+  infer_meta :
+    func : WhereInferMeta
+    spmd_rule: WhereInferSpmd
+  kernel :
+    func : where
+  interfaces : paddle::dialect::InferSymbolicShapeInterface
+
 - op : slice
   args : (Tensor x, int64_t[] axes, int64_t[] starts, int64_t[] ends, int64_t[] infer_flags, int64_t[] decrease_axis)
   output : Tensor

paddle/cinn/hlir/dialect/operator/transforms/pd_to_cinn_pass.cc

@@ -1068,6 +1068,24 @@ class SigmoidOpPattern
     rewriter.EraseOp(op);
   }
 };
+
+class WhereOpPattern : public pir::OpRewritePattern<paddle::dialect::WhereOp> {
+ public:
+  using pir::OpRewritePattern<paddle::dialect::WhereOp>::OpRewritePattern;
+
+  bool MatchAndRewrite(paddle::dialect::WhereOp op,
+                       pir::PatternRewriter &rewriter) const override {
+    auto select_op = rewriter.Build<cinn::dialect::SelectOp>(
+        op->operand_source(0), op->operand_source(1), op->operand_source(2));
+
+    rewriter.ReplaceAllUsesWith(op.result(0), select_op.result(0));
+
+    rewriter.EraseOp(op);
+
+    return true;
+  }
+};
+
 class GatherOpPattern
     : public pir::OpRewritePattern<paddle::dialect::GatherOp> {
  public:
@@ -1132,6 +1150,7 @@ pir::RewritePatternSet PdOpToCinnOpPass::InitializePatterns(
   ps.Add<UnsqueezeOpPattern>(context);
   ps.Add<SigmoidOpPattern>(context);
   ps.Add<GatherOpPattern>(context);
+  ps.Add<WhereOpPattern>(context);
   ps.Add<FlattenOpPattern>(context);
 
   return ps;

paddle/cinn/hlir/op/nn.cc

@@ -2253,6 +2253,70 @@ std::shared_ptr<OpStrategy> StrategyForSelect(
   return strategy;
 }
 
+std::shared_ptr<OpStrategy> StrategyForSelectSymbolic(
+    const framework::NodeAttr &attrs,
+    const std::vector<ir::Tensor> &inputs,
+    const std::vector<Type> &out_type,
+    const std::vector<std::vector<ir::Dim>> &output_shapes,
+    const Target &target) {
+  framework::CINNCompute select_compute([=](lang::Args args,
+                                            lang::RetValue *ret) {
+    PADDLE_ENFORCE_EQ(
+        !args.empty(),
+        true,
+        ::common::errors::InvalidArgument(
+            "The input argument of select compute is empty! Please check."));
+    CINNValuePack pack_args = args[0];
+    PADDLE_ENFORCE_GE(pack_args.size(),
+                      3U,
+                      ::common::errors::InvalidArgument(
+                          "at least three input tensor for select compute."));
+    Expr condition = pack_args[0];
+    Expr true_value = pack_args[1];
+    Expr false_value = pack_args[2];
+    PADDLE_ENFORCE_NE(condition.as_tensor(),
+                      nullptr,
+                      ::common::errors::InvalidArgument(
+                          "The condation arg's type should be Tensor."));
+    PADDLE_ENFORCE_NE(true_value.as_tensor(),
+                      nullptr,
+                      ::common::errors::InvalidArgument(
+                          "The true_value arg's type should be Tensor."));
+    PADDLE_ENFORCE_NE(false_value.as_tensor(),
+                      nullptr,
+                      ::common::errors::InvalidArgument(
+                          "The false_value arg's type should be Tensor."));
+    PADDLE_ENFORCE_EQ(pack_args.size(),
+                      4U,
+                      ::common::errors::InvalidArgument(
+                          "The size of inputs must be equal to 4."));
+    PADDLE_ENFORCE_EQ(pack_args[3].is_string(),
+                      true,
+                      ::common::errors::InvalidArgument(
+                          "The name arg's type should be string."));
+    std::string tensor_name = pack_args[3].operator std::string();
+
+    auto out = pe::Select(condition.as_tensor_ref(),
+                          true_value.as_tensor_ref(),
+                          false_value.as_tensor_ref(),
+                          tensor_name);
+    auto stages = CreateStages({condition.as_tensor_ref(),
+                                true_value.as_tensor_ref(),
+                                false_value.as_tensor_ref(),
+                                out});
+    *ret = CINNValuePack{{CINNValue(out), CINNValue(stages)}};
+  });
+
+  auto strategy = std::make_shared<framework::OpStrategy>();
+  PADDLE_ENFORCE_NE(out_type.size(),
+                    0U,
+                    ::common::errors::InvalidArgument(
+                        "Out_type of select op is empty! Please check."));
+  strategy->AddImpl(
+      select_compute, lang::PackedFunc(), "strategy.select.x86", 1);
+  return strategy;
+}
+
 std::vector<framework::shape_t> InferShapeForSelect(
     const std::vector<framework::shape_t> &inputs_shape,
     const framework::AttrMapType &attrs) {
@@ -2674,6 +2738,8 @@ CINN_REGISTER_HELPER(nn_ops) {
       .set_num_outputs(1)
       .set_attr<cinn::hlir::framework::StrategyFunction>(
           "CINNStrategy", cinn::hlir::op::StrategyForSelect)
+      .set_attr<cinn::hlir::framework::StrategyFunctionSymbolic>(
+          "CINNStrategySymbolic", cinn::hlir::op::StrategyForSelectSymbolic)
       .set_attr("infershape",
                 MakeOpFunction(cinn::hlir::op::InferShapeForSelect))
       .set_attr("inferdtype",

paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/same_operands_result.cc

@@ -117,6 +117,7 @@ OP_SAME_OPERANDS_AND_RESULT(Scale_)
 OP_SAME_OPERANDS_AND_RESULT(ScatterNdAdd)
 OP_SAME_OPERANDS_AND_RESULT(Scatter)
 OP_SAME_OPERANDS_AND_RESULT(Scatter_)
+OP_SAME_OPERANDS_AND_RESULT(Select)
 OP_SAME_OPERANDS_AND_RESULT(Sign)
 OP_SAME_OPERANDS_AND_RESULT(Sin)
 OP_SAME_OPERANDS_AND_RESULT(Sin_)
@@ -178,6 +179,7 @@ bool ScaleOpInferSymbolicShape(pir::Operation *op,
 namespace cinn::dialect {
 using paddle::dialect::ReverseOpInferSymbolicShape;
 using paddle::dialect::ScaleOpInferSymbolicShape;
+using paddle::dialect::SelectOpInferSymbolicShape;
 }  // namespace cinn::dialect
 
 #undef OP_SAME_OPERANDS_AND_RESULT

paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/same_operands_result.h

@@ -109,6 +109,7 @@ OP_DECLARE_INFER_SYMBOLIC_SHAPE(Scale_)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(ScatterNdAdd)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(Scatter)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(Scatter_)
+OP_DECLARE_INFER_SYMBOLIC_SHAPE(Select)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(Sign)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(Sin)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(Sin_)
@@ -134,4 +135,5 @@ OP_DECLARE_INFER_SYMBOLIC_SHAPE(Sigmoid_)
 namespace cinn::dialect {
 using paddle::dialect::ReverseOpInferSymbolicShape;
 using paddle::dialect::ScaleOpInferSymbolicShape;
+using paddle::dialect::SelectOpInferSymbolicShape;
 }  // namespace cinn::dialect

paddle/phi/infermeta/multiary.cc

@@ -4413,20 +4413,52 @@ void WhereInferMeta(const MetaTensor& condition,
   auto x_dims = x.dims();
   auto y_dims = y.dims();
   PADDLE_ENFORCE_EQ(
-      cond_dims,
-      x_dims,
+      cond_dims.size(),
+      x_dims.size(),
       phi::errors::InvalidArgument(
           "The dims of Inputs(Condition) and Inputs(X) should be same. "
-          "But received Condition's shape is [%s], X's shape is [%s]",
-          cond_dims,
-          x_dims));
-  PADDLE_ENFORCE_EQ(x_dims,
-                    y_dims,
+          "But received Condition's rank is [%d], X's rank is [%d]",
+          cond_dims.size(),
+          x_dims.size()));
+  size_t cond_dims_size = static_cast<size_t>(cond_dims.size());
+  for (size_t i = 0; i < cond_dims_size; ++i) {
+    if (cond_dims[i] == -1 || x_dims[i] == -1) {
+      continue;
+    }
+    PADDLE_ENFORCE_EQ(
+        cond_dims[i],
+        x_dims[i],
+        phi::errors::InvalidArgument(
+            "The [%d] th of Inputs(Condition) and Inputs(X) should be same. "
+            "But received Condition's shape is [%d], X's shape is [%d]",
+            i,
+            cond_dims[i],
+            x_dims[i]));
+  }
+
+  PADDLE_ENFORCE_EQ(x_dims.size(),
+                    y_dims.size(),
                     phi::errors::InvalidArgument(
                         "The dims of Inputs(X) and Inputs(Y) should be same. "
-                        "But received X's shape is [%s], Y's shape is [%s]",
-                        x_dims,
-                        y_dims));
+                        "But received X's shape is [%d], Y's shape is [%d]",
+                        x_dims.size(),
+                        y_dims.size()));
+  size_t x_dims_size = static_cast<size_t>(x_dims.size());
+  for (size_t i = 0; i < x_dims_size; ++i) {
+    if (x_dims[i] == -1 || y_dims[i] == -1) {
+      continue;
+    }
+    PADDLE_ENFORCE_EQ(
+        x_dims[i],
+        y_dims[i],
+        phi::errors::InvalidArgument(
+            "The [%d] th of Inputs(X) and Inputs(Y) should be same. "
+            "But received X's shape is [%s], Y's shape is [%s]",
+            i,
+            x_dims[i],
+            y_dims[i]));
+  }
+
   out->share_meta(x);
 }
 

test/ir/pir/cinn/inference/test_llama_postprocess.py

@@ -90,8 +90,8 @@ def prepare_data(self):
         self.input_ids = paddle.randint(0, 512, [1, 32], dtype="int64")
 
     def check_jit_kernel_info(self, static_fn):
-        utils.check_jit_kernel_number(static_fn, 10)
-        utils.check_jit_kernel_structure(static_fn, {utils.JIT_KERNEL_NAME: 10})
+        utils.check_jit_kernel_number(static_fn, 8)
+        utils.check_jit_kernel_structure(static_fn, {utils.JIT_KERNEL_NAME: 8})
 
     def eval(self, use_cinn):
         paddle.seed(2024)

test/ir/pir/cinn/sub_graphs/test_sub_graph_where.py

@@ -0,0 +1,71 @@
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+import numpy as np
+
+import paddle
+
+
+class WhereCase(paddle.nn.Layer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(
+        self,
+        cond,
+        true_branch,
+        false_branch,
+    ):
+        return paddle.tensor.where(cond, true_branch.sin(), false_branch)
+
+
+class TestWhere(unittest.TestCase):
+    def setUp(self):
+        self.inputs = (
+            paddle.rand(shape=[16, 16], dtype=paddle.float32).cast("bool"),
+            paddle.rand(shape=[16, 16], dtype=paddle.float32),
+            paddle.rand(shape=[16, 16], dtype=paddle.float32),
+        )
+
+    def train(self, net, to_static, with_prim=False, with_cinn=False):
+        if to_static:
+            paddle.set_flags({'FLAGS_prim_all': with_prim})
+            if with_cinn:
+                build_strategy = paddle.static.BuildStrategy()
+                build_strategy.build_cinn_pass = True
+                net = paddle.jit.to_static(
+                    net, build_strategy=build_strategy, full_graph=True
+                )
+            else:
+                net = paddle.jit.to_static(net, full_graph=True)
+        paddle.seed(123)
+        outs = net(*self.inputs)
+        return outs
+
+    def test_where(self):
+        net = WhereCase()
+        st_out = self.train(net, to_static=True)
+        cinn_out = self.train(
+            net, to_static=True, with_prim=True, with_cinn=True
+        )
+        for st, cinn in zip(
+            paddle.utils.flatten(st_out), paddle.utils.flatten(cinn_out)
+        ):
+            np.testing.assert_allclose(st.numpy(), cinn.numpy(), atol=1e-8)
+
+
+if __name__ == '__main__':
+    unittest.main()